Depth Map Upsampling Using Segmentation and Edge Information

Abstract

A depth upsampling method based on Markov Random Field is proposed, considering the depth and color information. First, the initial interpolated depth map is inaccurate and oversmooth, we use a rectangle window centered on every pixel to search the maximum and minimum depth value of the depth map to find out the edge pixels. Then, we use the depth information to guide the segmentation of the color image and build different data terms and smoothness terms for the edge and non-edge pixels. The result depth map is piecewise smooth and the edge is sharp. In the meanwhile, the result is good where the color information is consistent while the depth is not or where the depth information is consistent while the color is not. Experiments show that the proposed method performs better than other upsampling methods in terms of mean absolute difference (MAD).